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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 6 of 6 (0.037 seconds)Spelling suggestions: "subject:"arzneiverordnung"" "subject:"düngeverordnung""
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Grundprobleme der Zulassung besonders gefährlicher Stoffe in der REACH-Verordnung /Funke, Astrid M. January 1900 (has links)
Universiẗat, Diss.--Augsburg, 2007.
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Analyse reaktiver Toxizitätspotentiale organischer Elektrophile im Chemoassay mit 4-NitrothiophenolHiltrop, Rebecca 05 February 2016 (has links) (PDF)
Zur Bestimmung der toxizitätsrelevanten Thiolreaktivität wurde ein Chemoassay mit dem Modellnukleophil 4-Nitrothiophenol (NBT) entwickelt. Es wurden die Reaktionsgeschwindigkeitskonstanten kNBT für insgesamt 145 Verbindungen aus verschiedenen Stoffklassen bestimmt. Ein Modell zur Berücksichtigung der Flüchtigkeit der Elektrophile bei der Berechnung von kNBT wurde entwickelt. Außerdem wurde der Einfluss des pH-Werts auf die Thiolreaktivität unter reaktionsmechanistischen Gesichtspunkten diskutiert. Die NBT-Reaktivität wurde mit der Reaktivität gegenüber anderen toxizitätsrelevanten Nukleophilen verglichen. Zur Einordnung der Thiolreaktivität in den toxikologischen Zusammenhang wurden die Korrelationen zwischen kNBT und ausgewählten toxikologischen Endpunkten betrachtet. Am Beispiel der aquatischen Toxizität im Bioassay mit Tetrahymena pyriformis konnten stoffklassenspezifische Modelle zur Beschreibung der absoluten Toxizität log EC50 und der Toxizitätserhöhung log Te mit guter bis sehr guter Vorhersagekraft abgeleitet werden.
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Analyse reaktiver Toxizitätspotentiale organischer Elektrophile im Chemoassay mit 4-NitrothiophenolHiltrop, Rebecca 15 December 2015 (has links)
Zur Bestimmung der toxizitätsrelevanten Thiolreaktivität wurde ein Chemoassay mit dem Modellnukleophil 4-Nitrothiophenol (NBT) entwickelt. Es wurden die Reaktionsgeschwindigkeitskonstanten kNBT für insgesamt 145 Verbindungen aus verschiedenen Stoffklassen bestimmt. Ein Modell zur Berücksichtigung der Flüchtigkeit der Elektrophile bei der Berechnung von kNBT wurde entwickelt. Außerdem wurde der Einfluss des pH-Werts auf die Thiolreaktivität unter reaktionsmechanistischen Gesichtspunkten diskutiert. Die NBT-Reaktivität wurde mit der Reaktivität gegenüber anderen toxizitätsrelevanten Nukleophilen verglichen. Zur Einordnung der Thiolreaktivität in den toxikologischen Zusammenhang wurden die Korrelationen zwischen kNBT und ausgewählten toxikologischen Endpunkten betrachtet. Am Beispiel der aquatischen Toxizität im Bioassay mit Tetrahymena pyriformis konnten stoffklassenspezifische Modelle zur Beschreibung der absoluten Toxizität log EC50 und der Toxizitätserhöhung log Te mit guter bis sehr guter Vorhersagekraft abgeleitet werden.
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Development of a computational consensus model for the in silico prediction of the skin sensitising potential of organic chemicals in the context of REACHHillebrand, Marcus 27 September 2018 (has links)
Die Hautsensibilisierung (Typ 4 Hautallergie) nimmt in der Toxizitätsbewertung einen wichtigen Stellenwert ein, was u.a. daran zu sehen ist, dass sie unter dem europäischen Chemikaliengesetz REACH schon sehr früh, d.h. ab einer Jahrestonne, abgeprüft werden soll. Die Dissertation untersucht, ob die derzeit im Tierversuch stattfindende Toxizitätsprüfung durch computerchemische Methoden ersetzt werden kann. Dazu wurde eine Datenbank aus über 2000 Stoffen erstellt, aus der wichtige Unterschiede zwischen den eingesetzten Tiermodellen herausgelesen werden konnten. In den Untersuchungen trat auch zu Tage, dass – entgegen vorheriger Annahmen – die Bioverfügbarkeit, d.h. die Aufnahme von Substanzen über die Haut, im Tierversuch nur eine untergeordnete Rolle spielt. Zudem ist eine Abschätzung des hautsensibilisierenden Effekts von Stoffen anhand eines Read-across (Interpolation aus strukturähnlichen Verbindungen) und von Strukturalarmen (Substrukturelemente als Indikatoren für einen bestimmten Effekt) möglich. Wenn beide Ansätze im Rahmen einer Konsensmodellierung miteinander verschränkt werden, ergibt sich sogar eine gute Vorhersagestatistik. / Skin sensitisation (type 4 skin allergy) is an important parameter in the toxicity assessment of chemicals, which is underlined by the fact that it is evaluated even at the lowest tonnage (1 t/a), which can be registered under the european chemicals regulation (REACH). In this thesis it was investigated if the currently used animal models can be replace or refined with computational (in silico toxicological) methods. In this regard a data base consisting of about 2000 substances was build. With its data important differences between the currently applied animal tests could be derived. Furthermore, the investigation found that – in contrast to previous assumptions – the bioavailability of a chemical compound, i.e. the uptake via the skin, has only a minor impact on the test result of the evaluated animal models. Moreover, it was demonstated that the skin sensitising potential of chemicals can be predicted by read-across (interpolation with structurally similar substances) and with structural alerts (substructural elements which indicate a particular effect). Combining both prediction methods with consensus modelling lead to a good prediction regarding the question whether a particular chemical compound is a sensitiser or not.
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Semi-automated Ontology Generation for Biocuration and Semantic SearchWächter, Thomas 01 February 2011 (has links) (PDF)
Background:
In the life sciences, the amount of literature and experimental data grows at a tremendous rate. In order to effectively access and integrate these data, biomedical ontologies – controlled, hierarchical vocabularies – are being developed.
Creating and maintaining such ontologies is a difficult, labour-intensive, manual process. Many computational methods which can support ontology construction have been proposed in the past. However, good, validated systems are largely missing.
Motivation:
The biocuration community plays a central role in the development of ontologies. Any method that can support their efforts has the potential to have a huge impact in the life sciences.
Recently, a number of semantic search engines were created that make use of biomedical ontologies for document retrieval. To transfer the technology to other knowledge domains, suitable ontologies need to be created. One area where ontologies may prove particularly useful is the search for alternative methods to animal testing, an area where comprehensive search is of special interest to determine the availability or unavailability of alternative methods.
Results:
The Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG) developed in this thesis is a system which supports the creation and extension of ontologies by semi-automatically generating terms, definitions, and parent-child relations from text in PubMed, the web, and PDF repositories. The system is seamlessly integrated into OBO-Edit and Protégé, two widely used ontology editors in the life sciences. DOG4DAG generates terms by identifying statistically significant noun-phrases in text. For definitions and parent-child relations it employs pattern-based web searches. Each generation step has been systematically evaluated using manually validated benchmarks. The term generation leads to high quality terms also found in manually created ontologies. Definitions can be retrieved for up to 78% of terms, child ancestor relations for up to 54%. No other validated system exists that achieves comparable results.
To improve the search for information on alternative methods to animal testing an ontology has been developed that contains 17,151 terms of which 10% were newly created and 90% were re-used from existing resources. This ontology is the core of Go3R, the first semantic search engine in this field. When a user performs a search query with Go3R, the search engine expands this request using the structure and terminology of the ontology. The machine classification employed in Go3R is capable of distinguishing documents related to alternative methods from those which are not with an F-measure of 90% on a manual benchmark. Approximately 200,000 of the 19 million documents listed in PubMed were identified as relevant, either because a specific term was contained or due to the automatic classification. The Go3R search engine is available on-line under www.Go3R.org.
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Semi-automated Ontology Generation for Biocuration and Semantic SearchWächter, Thomas 27 October 2010 (has links)
Background:
In the life sciences, the amount of literature and experimental data grows at a tremendous rate. In order to effectively access and integrate these data, biomedical ontologies – controlled, hierarchical vocabularies – are being developed.
Creating and maintaining such ontologies is a difficult, labour-intensive, manual process. Many computational methods which can support ontology construction have been proposed in the past. However, good, validated systems are largely missing.
Motivation:
The biocuration community plays a central role in the development of ontologies. Any method that can support their efforts has the potential to have a huge impact in the life sciences.
Recently, a number of semantic search engines were created that make use of biomedical ontologies for document retrieval. To transfer the technology to other knowledge domains, suitable ontologies need to be created. One area where ontologies may prove particularly useful is the search for alternative methods to animal testing, an area where comprehensive search is of special interest to determine the availability or unavailability of alternative methods.
Results:
The Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG) developed in this thesis is a system which supports the creation and extension of ontologies by semi-automatically generating terms, definitions, and parent-child relations from text in PubMed, the web, and PDF repositories. The system is seamlessly integrated into OBO-Edit and Protégé, two widely used ontology editors in the life sciences. DOG4DAG generates terms by identifying statistically significant noun-phrases in text. For definitions and parent-child relations it employs pattern-based web searches. Each generation step has been systematically evaluated using manually validated benchmarks. The term generation leads to high quality terms also found in manually created ontologies. Definitions can be retrieved for up to 78% of terms, child ancestor relations for up to 54%. No other validated system exists that achieves comparable results.
To improve the search for information on alternative methods to animal testing an ontology has been developed that contains 17,151 terms of which 10% were newly created and 90% were re-used from existing resources. This ontology is the core of Go3R, the first semantic search engine in this field. When a user performs a search query with Go3R, the search engine expands this request using the structure and terminology of the ontology. The machine classification employed in Go3R is capable of distinguishing documents related to alternative methods from those which are not with an F-measure of 90% on a manual benchmark. Approximately 200,000 of the 19 million documents listed in PubMed were identified as relevant, either because a specific term was contained or due to the automatic classification. The Go3R search engine is available on-line under www.Go3R.org.
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